Learning to recognize thoracic disease in chest x-rays with knowledge-guided deep zoom neural networks

K Wang, X Zhang, S Huang, F Chen, X Zhang… - IEEE …, 2020 - ieeexplore.ieee.org
Automatic and accurate thorax disease diagnosis in Chest X-ray (CXR) image plays an
essential role in clinical assist analysis. However, due to its imaging noise regions and the …

Contralaterally enhanced networks for thoracic disease detection

G Zhao, C Fang, G Li, L Jiao… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
Identifying and locating diseases in chest X-rays are very challenging, due to the low visual
contrast between normal and abnormal regions, and distortions caused by other …

Weakly supervised thoracic disease localization via disease masks

HG Jung, WJ Nam, HW Kim, SW Lee - Neurocomputing, 2023 - Elsevier
To enable a deep learning-based system to be used in the medical domain as a computer-
aided diagnosis system, it is essential to not only classify diseases but also present the …

Computer-aided tuberculosis diagnosis with attribute reasoning assistance

C Pan, G Zhao, J Fang, B Qi, J Liu, C Fang… - … Conference on Medical …, 2022 - Springer
Although deep learning algorithms have been intensively developed for computer-aided
tuberculosis diagnosis (CTD), they mainly depend on carefully annotated datasets, leading …

A Review on Deep Learning Methods for Chest X-Ray based Abnormality Detection and Thoracic Pathology Classification

J Rocha, AM Mendonça, A Campilho - U. Porto Journal of …, 2021 - ijooes.fe.up.pt
Backed by more powerful computational resources and optimized training routines, deep
learning models have proven unprecedented performance and several benefits to extract …